Title: Long-term priors influence visual perception through recruitment of long-range feedback
Abstract Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors’ influence on perception and provide constraints on theories about long-term priors’ influence on perception. more »« less
DeStefano, Isabella; Vul, Edward; Brady, Timothy F.
(, Proceedings of the Annual Conference of the Cognitive Science Society)
null
(Ed.)
Existing knowledge shapes and distorts our memories, serving as a prior for newly encoded information. Here, we investigate the role of stable long-term priors (e.g. categorical knowledge) in conjunction with priors arising from recently encountered information (e.g. ’serial dependence’) in visual working memory for color. We use an iterated reproduction paradigm to allow a model-free assessment of the role of such priors. In Experiment 1, we find that participants’ reports reliably converge to certain areas of color space, but that this convergence is largely distinct for different individuals, suggesting responses are biased by more than just shared category knowledge. In Experiment 2, we explicitly manipulate trial n-1 and find recent history plays a major role in participants’ reports. Thus, we find that both global prior knowledge and recent trial information have biasing influences on visual working memory, demonstrating an important role for both shortand long-term priors in actively maintained information.
Zhu, Michael; Hardstone, Richard; He, Biyu J.
(, Scientific Reports)
Abstract Ambiguous images elicit bistable perception, wherein periods of momentary perceptual stability are interrupted by sudden perceptual switches. When intermittently presented, ambiguous images trigger a perceptual memory trace in the intervening blank periods. Understanding the neural bases of perceptual stability and perceptual memory during bistable perception may hold clues for explaining the apparent stability of visual experience in the natural world, where ambiguous and fleeting images are prevalent. Motivated by recent work showing the involvement of the right inferior frontal gyrus (rIFG) in bistable perception, we conducted a transcranial direct-current stimulation (tDCS) study with a double-blind, within-subject cross-over design to test a potential causal role of rIFG in these processes. Subjects viewed ambiguous images presented continuously or intermittently while under EEG recording. We did not find any significant tDCS effect on perceptual behavior. However, the fluctuations of oscillatory power in the alpha and beta bands predicted perceptual stability, with higher power corresponding to longer percept durations. In addition, higher alpha and beta power predicted enhanced perceptual memory during intermittent viewing. These results reveal a unified neurophysiological mechanism sustaining perceptual stability and perceptual memory when the visual system is faced with ambiguous input.
A promising approach to solving challenging long-horizon tasks has been to extract behavior priors (skills) by fitting generative models to large offline datasets of demonstrations. However, such generative models inherit the biases of the underlying data and result in poor and unusable skills when trained on imperfect demonstration data. To better align skill extraction with human intent we present Skill Preferences (SkiP), an algorithm that learns a model over human preferences and uses it to extract human-aligned skills from offline data. After extracting human-preferred skills, SkiP also utilizes human feedback to solve downstream tasks with RL. We show that SkiP enables a simulated kitchen robot to solve complex multi-step manipulation tasks and substantially outperforms prior leading RL algorithms with human preferences as well as leading skill extraction algorithms without human preferences.
Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus – a tritone pair – to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair’s perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch representations and taking their distance in the circular Shepard tone space predicts theoppositeof the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch and pitch-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.
Abstract Number sense is fundamental to the development of numerical problem‐solving skills. In early childhood, children establish associations between non‐symbolic (e.g., a set of dots) and symbolic (e.g., Arabic numerals) representations of quantity. The developmental estrangement theory proposes that the relationship between non‐symbolic and symbolic representations of quantity evolves with age, with increased dissociation across development. Consistent with this theory, recent research suggests that cross‐format neural representational similarity (NRS) between non‐symbolic and symbolic quantities is correlated with arithmetic fluency in children but not in adolescents. However, it is not known if short‐term training (STT) can induce similar changes as long‐term development. In this study, children aged 7–10 years underwent a theoretically motivated 4‐week number sense training. Using multivariate neural pattern analysis, we investigated whether short‐term learning could modify the relation between cross‐format NRS and arithmetic skills. Our results revealed a significant correlation between cross‐format NRS and arithmetic fluency in distributed brain regions, including the parietal and prefrontal cortices, prior to training. However, this association was no longer observed after training, and multivariate predictive models confirmed these findings. Our findings provide evidence that intensive STT during early childhood can promote behavioral improvements and neural plasticity that resemble and recapitulate long‐term neurodevelopmental changes that occur from childhood to adolescence. More generally, our study contributes to our understanding of the malleability of number sense and highlights the potential for targeted interventions to shape neurodevelopmental trajectories in early childhood. Research HighlightsWe tested the hypothesis that short‐term number sense training induces the dissociation of symbolic numbers from non‐symbolic representations of quantity in children.We leveraged a theoretically motivated intervention and multivariate pattern analysis to determine training‐induced neurocognitive changes in the relation between number sense and arithmetic problem‐solving skills.Neural representational similarity between non‐symbolic and symbolic quantity representations was correlated with arithmetic skills before training but not after training.Short‐term training recapitulates long‐term neurodevelopmental changes associated with numerical problem‐solving from childhood to adolescence.
@article{osti_10360037,
place = {Country unknown/Code not available},
title = {Long-term priors influence visual perception through recruitment of long-range feedback},
url = {https://par.nsf.gov/biblio/10360037},
DOI = {10.1038/s41467-021-26544-w},
abstractNote = {Abstract Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors’ influence on perception and provide constraints on theories about long-term priors’ influence on perception.},
journal = {Nature Communications},
volume = {12},
number = {1},
publisher = {Nature Publishing Group},
author = {Hardstone, Richard and Zhu, Michael and Flinker, Adeen and Melloni, Lucia and Devore, Sasha and Friedman, Daniel and Dugan, Patricia and Doyle, Werner K. and Devinsky, Orrin and He, Biyu J.},
}
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